from sklearn_benchmarks.report import Reporting, ReportingHpo, print_time_report, print_env_info
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
scikit-learn vs. scikit-learn-intelex (Intel® oneAPI) benchmarks: perfect hyperparameters match¶print_time_report()
sklearnex_KMeans_short: 0h 0m 1s
sklearnex_Ridge: 0h 0m 2s
KMeans_short: 0h 0m 3s
sklearnex_LogisticRegression: 0h 0m 4s
sklearnex_KMeans_tall: 0h 0m 9s
Ridge: 0h 0m 12s
LogisticRegression: 0h 0m 22s
KMeans_tall: 0h 0m 25s
sklearnex_KNeighborsClassifier_kd_tree: 0h 0m 30s
KNeighborsClassifier_kd_tree: 0h 2m 54s
sklearnex_KNeighborsClassifier: 0h 3m 10s
catboost_lossguide: 0h 5m 2s
xgboost: 0h 5m 10s
lightgbm: 0h 5m 12s
HistGradientBoostingClassifier: 0h 5m 16s
catboost_symmetric: 0h 5m 33s
KNeighborsClassifier: 0h 34m 32s
total: 1h 8m 44s
print_env_info()
{
"system_info": {
"python": "3.8.10 | packaged by conda-forge | (default, May 11 2021, 07:01:05) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.8.0-1036-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1.3",
"setuptools": "49.6.0.post20210108",
"sklearn": "1.0.dev0",
"numpy": "1.21.0",
"scipy": "1.7.0",
"Cython": null,
"pandas": "1.3.0",
"matplotlib": "3.4.2",
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.15.so",
"prefix": "libopenblas",
"user_api": "blas",
"internal_api": "openblas",
"version": "0.3.15",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/python3.8/site-packages/scikit_learn.libs/libgomp-f7e03b3e.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
}
],
"cpu_count": 2
}
reporting = Reporting(config="config.yml")
reporting.run()
KNeighborsClassifier: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.191 | 0.0 | 4.187 | 0.0 | 1 | 5 | NaN | NaN | 0.508 | 0.0 | 0.376 | 0.0 | See | See |
| 3 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.143 | 0.0 | 5.595 | 0.0 | 1 | 1 | NaN | NaN | 0.496 | 0.0 | 0.288 | 0.0 | See | See |
| 6 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.138 | 0.0 | 5.796 | 0.0 | 1 | 100 | NaN | NaN | 0.497 | 0.0 | 0.278 | 0.0 | See | See |
| 9 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.131 | 0.0 | 6.107 | 0.0 | -1 | 1 | NaN | NaN | 0.499 | 0.0 | 0.263 | 0.0 | See | See |
| 12 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.134 | 0.0 | 5.984 | 0.0 | -1 | 5 | NaN | NaN | 0.499 | 0.0 | 0.268 | 0.0 | See | See |
| 15 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.130 | 0.0 | 6.155 | 0.0 | -1 | 100 | NaN | NaN | 0.501 | 0.0 | 0.260 | 0.0 | See | See |
| 18 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.062 | 0.0 | 0.257 | 0.0 | 1 | 5 | NaN | NaN | 0.116 | 0.0 | 0.537 | 0.0 | See | See |
| 21 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.063 | 0.0 | 0.253 | 0.0 | 1 | 1 | NaN | NaN | 0.115 | 0.0 | 0.550 | 0.0 | See | See |
| 24 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.061 | 0.0 | 0.262 | 0.0 | 1 | 100 | NaN | NaN | 0.115 | 0.0 | 0.530 | 0.0 | See | See |
| 27 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.063 | 0.0 | 0.255 | 0.0 | -1 | 1 | NaN | NaN | 0.116 | 0.0 | 0.542 | 0.0 | See | See |
| 30 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.066 | 0.0 | 0.242 | 0.0 | -1 | 5 | NaN | NaN | 0.117 | 0.0 | 0.564 | 0.0 | See | See |
| 33 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.066 | 0.0 | 0.243 | 0.0 | -1 | 100 | NaN | NaN | 0.116 | 0.0 | 0.568 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 22.900 | 0.226 | 0.0 | 0.023 | 1 | 5 | 0.795 | 0.950 | 2.280 | 0.012 | 10.045 | 0.112 | See | See |
| 2 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.214 | 0.005 | 0.0 | 0.214 | 1 | 5 | 1.000 | 1.000 | 0.091 | 0.001 | 2.337 | 0.058 | See | See |
| 4 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 13.643 | 0.065 | 0.0 | 0.014 | 1 | 1 | 0.692 | 0.823 | 2.227 | 0.019 | 6.125 | 0.061 | See | See |
| 5 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.211 | 0.002 | 0.0 | 0.211 | 1 | 1 | 1.000 | 1.000 | 0.097 | 0.015 | 2.169 | 0.341 | See | See |
| 7 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 22.786 | 0.079 | 0.0 | 0.023 | 1 | 100 | 0.933 | 0.950 | 2.375 | 0.041 | 9.596 | 0.170 | See | See |
| 8 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.213 | 0.002 | 0.0 | 0.213 | 1 | 100 | 1.000 | 1.000 | 0.092 | 0.001 | 2.305 | 0.032 | See | See |
| 10 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 25.277 | 0.530 | 0.0 | 0.025 | -1 | 1 | 0.692 | 0.823 | 2.291 | 0.021 | 11.032 | 0.253 | See | See |
| 11 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.194 | 0.022 | 0.0 | 0.194 | -1 | 1 | 1.000 | 1.000 | 0.092 | 0.000 | 2.110 | 0.234 | See | See |
| 13 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 34.056 | 0.000 | 0.0 | 0.034 | -1 | 5 | 0.795 | 0.718 | 2.290 | 0.013 | 14.874 | 0.082 | See | See |
| 14 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.200 | 0.021 | 0.0 | 0.200 | -1 | 5 | 1.000 | 1.000 | 0.094 | 0.003 | 2.128 | 0.236 | See | See |
| 16 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 33.889 | 0.000 | 0.0 | 0.034 | -1 | 100 | 0.933 | 0.718 | 2.288 | 0.027 | 14.812 | 0.174 | See | See |
| 17 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.197 | 0.024 | 0.0 | 0.197 | -1 | 100 | 1.000 | 1.000 | 0.093 | 0.001 | 2.121 | 0.254 | See | See |
| 19 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 21.260 | 0.043 | 0.0 | 0.021 | 1 | 5 | 0.989 | 0.982 | 0.426 | 0.003 | 49.949 | 0.400 | See | See |
| 20 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.024 | 0.000 | 0.0 | 0.024 | 1 | 5 | 1.000 | 1.000 | 0.007 | 0.001 | 3.468 | 0.458 | See | See |
| 22 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 10.372 | 0.034 | 0.0 | 0.010 | 1 | 1 | 0.976 | 0.981 | 0.360 | 0.003 | 28.797 | 0.266 | See | See |
| 23 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.016 | 0.000 | 0.0 | 0.016 | 1 | 1 | 1.000 | 1.000 | 0.007 | 0.000 | 2.414 | 0.128 | See | See |
| 25 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 21.370 | 0.047 | 0.0 | 0.021 | 1 | 100 | 0.994 | 0.982 | 0.427 | 0.002 | 50.067 | 0.280 | See | See |
| 26 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.025 | 0.000 | 0.0 | 0.025 | 1 | 100 | 1.000 | 1.000 | 0.007 | 0.001 | 3.334 | 0.560 | See | See |
| 28 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 22.605 | 0.266 | 0.0 | 0.023 | -1 | 1 | 0.976 | 0.981 | 0.366 | 0.001 | 61.782 | 0.755 | See | See |
| 29 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.025 | 0.004 | 0.0 | 0.025 | -1 | 1 | 1.000 | 1.000 | 0.007 | 0.000 | 3.498 | 0.590 | See | See |
| 31 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 32.789 | 0.000 | 0.0 | 0.033 | -1 | 5 | 0.989 | 0.974 | 0.363 | 0.005 | 90.239 | 1.189 | See | See |
| 32 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.032 | 0.002 | 0.0 | 0.032 | -1 | 5 | 1.000 | 1.000 | 0.007 | 0.001 | 4.511 | 0.614 | See | See |
| 34 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 32.825 | 0.000 | 0.0 | 0.033 | -1 | 100 | 0.994 | 0.974 | 0.361 | 0.003 | 90.913 | 0.852 | See | See |
| 35 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.032 | 0.002 | 0.0 | 0.032 | -1 | 100 | 1.000 | 1.000 | 0.007 | 0.001 | 4.609 | 0.913 | See | See |
KNeighborsClassifier_kd_tree: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.535 | 0.0 | 0.023 | 0.0 | -1 | 5 | NaN | NaN | 0.803 | 0.0 | 4.400 | 0.0 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.691 | 0.0 | 0.022 | 0.0 | -1 | 1 | NaN | NaN | 0.799 | 0.0 | 4.617 | 0.0 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.663 | 0.0 | 0.022 | 0.0 | 1 | 100 | NaN | NaN | 0.795 | 0.0 | 4.610 | 0.0 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.558 | 0.0 | 0.022 | 0.0 | 1 | 5 | NaN | NaN | 0.803 | 0.0 | 4.433 | 0.0 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.362 | 0.0 | 0.024 | 0.0 | 1 | 1 | NaN | NaN | 0.804 | 0.0 | 4.182 | 0.0 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.381 | 0.0 | 0.024 | 0.0 | -1 | 100 | NaN | NaN | 0.798 | 0.0 | 4.235 | 0.0 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.893 | 0.0 | 0.018 | 0.0 | -1 | 5 | NaN | NaN | 0.554 | 0.0 | 1.610 | 0.0 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.873 | 0.0 | 0.018 | 0.0 | -1 | 1 | NaN | NaN | 0.541 | 0.0 | 1.613 | 0.0 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.867 | 0.0 | 0.018 | 0.0 | 1 | 100 | NaN | NaN | 0.543 | 0.0 | 1.597 | 0.0 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.895 | 0.0 | 0.018 | 0.0 | 1 | 5 | NaN | NaN | 0.547 | 0.0 | 1.637 | 0.0 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.870 | 0.0 | 0.018 | 0.0 | 1 | 1 | NaN | NaN | 0.555 | 0.0 | 1.568 | 0.0 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.868 | 0.0 | 0.018 | 0.0 | -1 | 100 | NaN | NaN | 0.547 | 0.0 | 1.588 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.906 | 0.008 | 0.000 | 0.001 | -1 | 5 | 0.973 | 0.967 | 0.610 | 0.010 | 1.486 | 0.028 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 5 | 1.000 | 1.000 | 0.001 | 0.000 | 5.608 | 1.921 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.490 | 0.009 | 0.000 | 0.000 | -1 | 1 | 0.964 | 0.946 | 0.109 | 0.001 | 4.477 | 0.094 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 22.860 | 12.642 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 5.197 | 0.024 | 0.000 | 0.005 | 1 | 100 | 0.974 | 0.968 | 0.200 | 0.003 | 25.991 | 0.368 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.010 | 0.000 | 0.000 | 0.010 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 28.570 | 10.944 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 1.507 | 0.022 | 0.000 | 0.002 | 1 | 5 | 0.973 | 0.968 | 0.197 | 0.002 | 7.650 | 0.127 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 9.143 | 3.714 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.766 | 0.009 | 0.000 | 0.001 | 1 | 1 | 0.964 | 0.946 | 0.110 | 0.001 | 6.979 | 0.117 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 9.216 | 4.858 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.000 | 0.016 | 0.000 | 0.003 | -1 | 100 | 0.974 | 0.967 | 0.601 | 0.009 | 4.993 | 0.078 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.013 | 0.002 | 0.000 | 0.013 | -1 | 100 | 1.000 | 1.000 | 0.001 | 0.000 | 14.861 | 5.161 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.029 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.975 | 0.982 | 0.007 | 0.001 | 3.836 | 0.499 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 19.021 | 12.678 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.026 | 0.001 | 0.001 | 0.000 | -1 | 1 | 0.969 | 0.974 | 0.001 | 0.000 | 32.319 | 9.080 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 20.546 | 13.332 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.057 | 0.001 | 0.000 | 0.000 | 1 | 100 | 0.979 | 0.978 | 0.001 | 0.001 | 43.995 | 19.014 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 5.762 | 4.380 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.027 | 0.000 | 0.001 | 0.000 | 1 | 5 | 0.975 | 0.978 | 0.001 | 0.000 | 22.636 | 4.434 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 5.596 | 4.422 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.024 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.969 | 0.974 | 0.001 | 0.000 | 22.161 | 5.451 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 5.512 | 4.120 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.049 | 0.000 | 0.000 | 0.000 | -1 | 100 | 0.979 | 0.982 | 0.008 | 0.001 | 6.411 | 1.069 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 19.938 | 14.183 | See | See |
KMeans_tall: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.665 | 0.0 | 0.722 | 0.0 | random | NaN | 30 | NaN | 0.528 | 0.0 | 1.259 | 0.0 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.657 | 0.0 | 0.730 | 0.0 | k-means++ | NaN | 30 | NaN | 0.563 | 0.0 | 1.166 | 0.0 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 7.322 | 0.0 | 3.278 | 0.0 | random | NaN | 30 | NaN | 3.033 | 0.0 | 2.414 | 0.0 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 7.235 | 0.0 | 3.317 | 0.0 | k-means++ | NaN | 30 | NaN | 3.222 | 0.0 | 2.246 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.301 | 0.000 | random | 0.001 | 30 | 0.000 | 0.0 | 0.0 | 8.780 | 4.502 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.000 | 0.002 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 11.926 | 7.712 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.306 | 0.000 | k-means++ | 0.001 | 30 | 0.000 | 0.0 | 0.0 | 8.735 | 4.766 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.000 | 0.002 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 11.149 | 6.661 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 11.227 | 0.000 | random | 0.002 | 30 | 0.001 | 0.0 | 0.0 | 6.691 | 2.705 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.016 | 0.002 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 9.453 | 4.795 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 11.975 | 0.000 | k-means++ | 0.001 | 30 | 0.002 | 0.0 | 0.0 | 5.846 | 2.497 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.016 | 0.002 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 10.155 | 5.696 | See | See |
KMeans_short: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.106 | 0.0 | 0.030 | 0.0 | random | NaN | 20 | NaN | 0.039 | 0.0 | 2.712 | 0.0 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.292 | 0.0 | 0.011 | 0.0 | k-means++ | NaN | 20 | NaN | 0.101 | 0.0 | 2.878 | 0.0 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.261 | 0.0 | 0.614 | 0.0 | random | NaN | 20 | NaN | 0.148 | 0.0 | 1.760 | 0.0 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.726 | 0.0 | 0.220 | 0.0 | k-means++ | NaN | 20 | NaN | 0.401 | 0.0 | 1.812 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.001 | 0.131 | 0.000 | random | 0.001 | 20 | -0.001 | 0.001 | 0.0 | 3.954 | 1.227 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.000 | 0.000 | 0.002 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 10.794 | 6.408 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.001 | 0.129 | 0.000 | k-means++ | 0.000 | 20 | -0.002 | 0.001 | 0.0 | 3.730 | 1.043 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.000 | 0.000 | 0.002 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 10.908 | 6.615 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.003 | 0.000 | 5.193 | 0.000 | random | 0.366 | 20 | 0.265 | 0.001 | 0.0 | 2.444 | 0.388 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.000 | 0.010 | 0.002 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.020 | 3.699 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.003 | 0.000 | 5.483 | 0.000 | k-means++ | 0.260 | 20 | 0.299 | 0.001 | 0.0 | 2.385 | 0.337 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.000 | 0.010 | 0.002 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.208 | 3.749 | See | See |
LogisticRegression: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_informative | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [20] | 12.729 | 0.0 | [-0.09268799] | 0.000 | NaN | NaN | NaN | NaN | NaN | 2.166 | 0.0 | 5.877 | 0.0 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [27] | 0.920 | 0.0 | [-2.31968832] | 0.001 | NaN | NaN | NaN | NaN | NaN | 0.836 | 0.0 | 1.101 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_informative | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [20] | 0.000 | 0.0 | [45.48626955] | 0.0 | NaN | NaN | NaN | NaN | 0.571 | 0.000 | 0.0 | 0.823 | 0.310 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [20] | 0.000 | 0.0 | [0.15337835] | 0.0 | NaN | NaN | NaN | NaN | 0.000 | 0.000 | 0.0 | 0.543 | 0.530 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [27] | 0.002 | 0.0 | [111.85254272] | 0.0 | NaN | NaN | NaN | NaN | 0.320 | 0.003 | 0.0 | 0.579 | 0.078 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [27] | 0.000 | 0.0 | [19.58693334] | 0.0 | NaN | NaN | NaN | NaN | 0.000 | 0.001 | 0.0 | 0.141 | 0.091 | See | See |
Ridge: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_informative | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.205 | 0.0 | 0.391 | 0.0 | NaN | NaN | NaN | 0.210 | 0.0 | 0.974 | 0.0 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 10 | 42 | sklearn.datasets.make_regression | NaN | 1.610 | 0.0 | 0.497 | 0.0 | NaN | NaN | NaN | 0.286 | 0.0 | 5.629 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_informative | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.01 | 0.0 | 7.847 | 0.0 | NaN | NaN | 0.118 | 0.017 | 0.0 | 0.591 | 0.022 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.00 | 0.0 | 0.973 | 0.0 | NaN | NaN | NaN | 0.000 | 0.0 | 0.617 | 0.503 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.00 | 0.0 | 4.686 | 0.0 | NaN | NaN | 1.000 | 0.000 | 0.0 | 0.662 | 0.410 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.00 | 0.0 | 0.012 | 0.0 | NaN | NaN | NaN | 0.000 | 0.0 | 0.624 | 0.622 | See | See |